Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

Portable and stationary electrical generators became quite popular in Iraq soon after the shortage in national electrical
energy after 2003. Multi step risk assessment process is used in this study in the assessment of risks caused by
contamination of indoor air by lead particles emitted from domestic electrical generators. Two portable electrical
generators are tested under controlled indoor conditions (Radial LG (0.9 keV) fueled with benzene and oil and TigMax
(3 keV), fueled with benzene only). Lead particles in air were sampled by using portable dust sampler (Sniffer, L-30).
The atmospheric particulate sampling process is carried out in a flat located in the first floor of a three stories building
located in Baghdad

Two simple, rapid, and useful spectrophotometric methods were suggest or the determination of sulphadimidine sodium (SDMS) with and without using cloud point extraction technique in pure form and pharmaceutical preparation. The first  method was based on  diazotization of the Sulphdimidine Sodium drug by sodium nitrite at 5 ºC, followed by coupling with α –Naphthol in basic medium to form an orange colored product . The product was stabilized and its absorption was measured at 473 nm. Beer’s law was obeyed in the concentration range of (1-12) μg∙ml^-1. Sandell’s sensitivity was 0.03012 μg∙cm^-1, the detection limit was 0.0277 μg∙ml^-1, and the limit of Quantitation was 0.03605μg

This work studies the performance of zeolite permeable reactive barrier in removing cadmium from a contaminated shallow aquifer. Batch tests have been performed to characterize the equilibrium sorption properties of the zeolite in cadmium-containing aqueous solutions. A 1D numerical finite difference model has been developed to describe pollutant transport within groundwater taking pollutant sorption on the permeable reactive barrier (PRB), which is performed by Langmuir equation, into account. Numerical results show that the PRB starts to saturate after a period of time (~120 h) due to reduction of the retardation factor, indicating a decrease in the percentage of zeolite functionality. However, a reasonable agreement between model predict

This work deals with separation of the aromatic hydrocarbons benzene, toluene, and xylene (BTX) from reformate. The separation was examined using adsorption by molecular sieve zeolite 13X in a fixed bed process. The concentration of aromatic hydrocarbons in the influent and effluent streams was measured using gas chromatography. The effect of flow rate and bed length of adsorbent on the adsorption of multicomponent hydrocarbons and adsorption capacity of molecular sieve was studied. The tendency of aromatic hydrocarbons adsorption from reformate is in the order: benzene >toluene>xylenes.

In this work, the possibility of utilizing osmosis phenomenon to produce energy as a type of the renewable energy using Thin Film Composite Ultra Low Pressure membrane TFC-ULP was studied. Where by forward osmosis water passes through the membrane toward the concentrated brine solution, this will lead to raise the head of the high brine solution. This developed static head may be used to produce energy. The aim of the present work is to study the static head developed and the flux on the high brine water solution side when using forward and reverse osmosis membranes for an initial concentration range from 35-300 g/l for each type of membrane used at room temperature and pressure conditions, and finally calculating the maximum possible po

In the present work, the pollutants of the municipal wastewater are reduced using Chlorella vulgaris microalgae. The pollutants that were treated are: Total organic carbon (TOC), Chemical oxygen demand (COD), Nitrate (NO₃), and Phosphate (PO₄). Firstly, the treatment was achieved at atmospheric conditions (Temperature = 25^oC), pH 7 with time (1 – 48 h). To study the effect of other microorganisms on the reduction of pollutants, sterilized wastewater and unsterilized wastewater were used for two types of packing (cylindrical plastic and cubic polystyrene) as well as algae's broth (without packing), where the microalgae are grown on the packing then transported to the wastewater for treatment. Th